code: def forward(self, batch):
      batch.node_feature = torch.cat(
          [batch[name].float() for name in self.dim_dict], dim=1
      )
      return batch
  
imports: import logging
  import networkx
  import numpy
  import torch
  import torch.nn
  from deepsnap.graph import Graph
  import graphgym.register
  from graphgym.config import cfg
  from graphgym.contrib.transform.identity import compute_identity
label_desc: Use image node_id 3 for calling the Preprocess obj's underlying member method code with example usage: obj.forward(batch) and returns: batch